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  1. Home
  2. Case-Study

Optimizing Menus through Comprehensive Restaurant Data Scraping: A Case Study

This case study highlights our data scraping solutions for a popular food chain to handle daily operations, beat the competition, and deliver a customer-friendly experience. The client was eager to explore the benefits of ethical data scraping and how it can revolutionize their business toward profitable results.

Scrape-Restaurant-Data-To-Bring-High-Profits-In-Business

Project Requirement

We connected with the client, and they shared that with customers' changing interests and demands, they face challenges in meeting their expectations. They were looking for data-driven solutions to monitor the competitors and perform in-depth customer sentiment analysis at various locations of your restaurant chains. From menu designs, food trends, pricing strategies, offers, innovations, and other factors, they wanted to analyze such elements to understand the dynamic restaurant market.

Faced Challenges

As the client deals with various food chains of their restaurants, it is challenging to streamline the complete operations in every branch.

The restaurant team is already trying to introduce new innovations in food items but has failed to please the customers as expected. They wanted to understand the right approach to reaching potential audiences and optimize their marketing strategies to grab attention quickly.

Some challenges faced during building an ideal solution are:

  • The client must gather data from competitors, including menu items, customer preference, and competitor strategies in real-time, to build a scalable solution.
  • They wanted data from over 100+ resources globally, including food delivery platforms, social media, and competitor websites. Our adaptive scraping tools were up to the task, handling such updates without issues, providing the client with the data they needed.
  • Customer reviews and social media platforms contain unstructured data, which is challenging to analyze and requires advanced algorithms to organize the data.
  • The restaurant market is subject to constant changes, including seasonal menu changes and price updates, which requires our scripts to monitor the data regularly, ensuring its relevance for the client.

Solutions

  • We have a custom scraping infrastructure capable of handling unique data structures of food delivery platforms, social media, and competitor websites.
  • Robust data-cleaning algorithms help manage different data formats and extract consistent and reliable data sets for in-depth analysis.
  • To prevent rate-limiting issues, we controlled the count of requests made each second to ensure we did not hinder the target website performance.
  • Understanding competitors' pricing, seasonal menu items, and offers strategies helped them to optimize their offerings and deliver customer-friendly experiences in their food chains.

Impact

  • Customer Sentiment Analysis: The client gained valuable information about customer behavior and preferences through the data collected from publicly available platforms. This helped them to deliver a personalized experience and boost customer satisfaction.
  • Data-Driven Decisions: With our strong support, the client was empowered to build profitable strategies for menu updates and seasonal promotions, making them a famous brand name.
  • Operational Efficiency: We automated some processes such as data collection, cleaning, and analysis, ensuring better business operations for the client while reducing manual efforts and updating the restaurant services regularly per market trends.
  • Highly Scalable Solutions: Our client handled large-scale data sets as our scraping tools can extract data from multiple platforms and deliver structured data sets as required by a client for analysis.

Conclusion

The scraped data was shared in multiple formats as the client requested, allowing them to analyze the information hassle-free. New strategies boosted the customer satisfaction ratio and positive reviews of the menu offerings. Our client also evaluated the pricing strategies of different food items to understand upscale dining and affordable options for other locations.